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Discovering the underlying relationships among variables from temporal observations has been a longstanding challenge in numerous scientific disciplines, including biology, finance, and climate science. The dynamics of such systems are…

Machine Learning · Computer Science 2024-05-07 Benjie Wang , Joel Jennings , Wenbo Gong

The coefficient function of the leading differential operator is estimated from observations of a linear stochastic partial differential equation (SPDE). The estimation is based on continuous time observations which are localised in space.…

Statistics Theory · Mathematics 2021-03-30 Randolf Altmeyer , Markus Reiß

The measurement statistics for spatial and temporal quantum processes are produced through distinct mechanisms. Measurements that are space-like separated exhibit non-signaling behavior. However, time-like separated measurements can only…

Quantum Physics · Physics 2024-08-30 Zhian Jia , Dagomir Kaszlikowski

In this paper, we extend the standard formalism of quantum mechanics to a quantum theory for a total system including one internal measuring apparatus. The internality of the measuring apparatus implies that different decomposition of a…

Quantum Physics · Physics 2012-05-17 Wen-ge Wang

Extending discrete-time causal Prior-data Fitted Networks for time series to continuous time invites writing the mechanism as a stochastic differential equation (SDE) -- but if the SDE is integrated \emph{once per observation gap}, the…

Machine Learning · Computer Science 2026-05-29 Dennis Thumm , Ruben Wiedemann , Ying Chen

Theoretical tools used in processing continuous measurement records from real experiments to obtain quantum trajectories can easily lead to numerical errors due to a non-infinitesimal time resolution. In this work, we propose a systematic…

Quantum Physics · Physics 2024-12-16 Nattaphong Wonglakhon , Howard M. Wiseman , Areeya Chantasri

We study the invariant measures of infinite systems of stochastic differential equations (SDEs) indexed by the vertices of a regular tree. These invariant measures correspond to Gibbs measures associated with certain continuous…

Probability · Mathematics 2021-12-07 Daniel Lacker , Jiacheng Zhang

We introduce new entanglement measures on the set of density operators on tensor product Hilbert spaces. These measures are based on the greatest cross norm on the tensor product of the sets of trace class operators on Hilbert space. We…

Mathematical Physics · Physics 2015-06-26 Oliver Rudolph

Irregular sampling intervals and missing values in real-world time series data present challenges for conventional methods that assume consistent intervals and complete data. Neural Ordinary Differential Equations (Neural ODEs) offer an…

Machine Learning · Computer Science 2025-01-28 YongKyung Oh , Dong-Young Lim , Sungil Kim

We demonstrate in this paper that the probabilities for sequential measurements have features very different from those of single-time measurements. First, they cannot be modelled by a classical stochastic process. Second, they are…

Quantum Physics · Physics 2009-11-11 Charis Anastopoulos

We offer a spectral analysis for a class of transfer operators. These transfer operators arise for a wide range of stochastic processes, ranging from random walks on infinite graphs to the processes that govern signals and recursive wavelet…

Mathematical Physics · Physics 2018-02-14 Palle E. T. Jorgensen , Myung-Sin Song

Completely positive trace-preserving maps $S$, also known as quantum channels, arise in quantum physics as a description of how the density operator $\rho$ of a system changes in a given time interval, allowing not only for unitary…

Mathematical Physics · Physics 2024-11-25 Roderich Tumulka , Jonte Weixler

Stochastic differential equations (SDEs) provide a flexible framework for modeling temporal dynamics in partially observed systems. A central task is to calibrate such models from data, which requires inferring latent trajectories and…

Machine Learning · Statistics 2026-05-08 Yu Wang , Arnab Ganguly

These notes rigorously construct the stochastic integral of a Hilbert Space valued process driven by a Cylindrical Brownian Motion. We expand upon this stochastic calculus to present an introduction to stochastic differential equations in…

Probability · Mathematics 2023-09-15 Daniel Goodair

Partial trace is a very important mathematical operation in quantum mechanics. It is not only helpful in studying the subsystems of a composite quantum system but also used in computing a vast majority of quantum entanglement measures.…

Quantum Physics · Physics 2019-06-28 Pranay Barkataki , M. S. Ramkarthik

In recent years, higher-order trace formulas of operator functions have attracted considerable attention to a large part of the perturbation theory community. In this direction, we prove estimates for traces of higher-order derivatives of…

Functional Analysis · Mathematics 2023-07-25 Arup Chattopadhyay , Saikat Giri , Chandan Pradhan

The Stochastic Partial Differential Equation (SPDE) approach, now commonly used in spatial statistics to construct Gaussian random fields, is revisited from a mechanistic perspective based on the movement of microscopic particles, thereby…

Methodology · Statistics 2021-11-11 Lionel Roques , Denis Allard , Samuel Soubeyrand

In the present paper we consider the problem of description of an arbitrary generalized quantum measurement with outcomes in a measurable space. Analyzing the unitary invariants of a measuring process, we present the most general form of a…

Quantum Physics · Physics 2010-12-30 Elena R. Loubenets

Stochastic difference equations and a stochastic partial differential equation (SPDE) are simultaneously derived for the time-dependent neutron angular density in a general three-dimensional medium where the neutron angular density is a…

Numerical Analysis · Mathematics 2010-04-16 Edward J. Allen

Starting from the meaning of the conjugate of a complex Hilbert space, including a related application of the theorem of Fr\'{e}chet-Riesz (by which an analysis of semilinear operators can be reduced to - linear - operator theory) to a…

Functional Analysis · Mathematics 2026-01-05 Frank Oertel